Enterprises are racing to operationalize generative AI patterns that boost knowledge worker productivity. A key focus has been unlocking insights from unstructured data. So far, the most common approaches -- retrieval-augmented generation (RAG) and fine-tuning -- have centered on integrating unstructured data with large language models (LLMs). While effective for tasks like agent assistance to support asking questions from many long PDFs, these methods fall short when structured elements are embedded within unstructured documents, such as legal contracts, insurance claims, or invoices.

Session Topic: Gen AI & Agents
Activity Type: Technology Breakout
Industry: Cross Industry
Technical Level: Advanced Level
Product: watsonx.data
Role: Data Expert
Speaker(s): Dirk Deroos